Instructions to use microsoft/swin-tiny-patch4-window7-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-tiny-patch4-window7-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-tiny-patch4-window7-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/swin-tiny-patch4-window7-224") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-tiny-patch4-window7-224") - Inference
- Notebooks
- Google Colab
- Kaggle
Node: 'model/swin_transformer/tf_swin_model/swin/encoder/layers.1/blocks.0/Reshape_33' Input to reshape is a tensor with 3763200 values, but the requested shape requires a multiple of 20384
1
#4 opened about 2 years ago
by
JIRSTAYSOBER
Adding `safetensors` variant of this model
#3 opened almost 3 years ago
by
SFconvertbot
how to use swin v2?
2
#1 opened over 3 years ago
by
Bailey24